The “Level of Use” Index as a Tool to Assess Professional Development
Bibliographic record
Abstract
The “Level of Use of an Innovation" (LoU) and “Stages of Concern” (SoC) \nassessments are key components of the Concerns-Based Adoption Model (CBAM). \nThese tools can provide a clear articulation and characterization of the level of adoption \nof an organizational innovation in educational technology. An adaptation of the LoU was \nused to assess changes in understanding of and competence with educational technologies \nby participants in a graduate level course focused on the use of emergent technologies in \nprofessional development. The instrument reflected the criteria framework of the original \nLoU assessment tool, but was adapted to utilize a specifically structured self-reporting \nscale of the “level of use” index to promote collaborative self-reflection. Growth in \nknowledge of, and confidence with, specific emergent technologies is clearly indicated \nby the results, thus supporting the use of collaborative reflection and assessment of the \nprofessional development process to foster professional growth.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".